To date, four waves, or generations, of nanotechnology have evolved. The first generation was comprised mainly of developments involving chemical composition, such as new nanomaterials. The second generation developed simple tubes and filaments by positioning atoms from the ground up with novel machinery. The third generation developed nanodevices that perform specific functions, such as nanoparticles for the delivery of chemicals. Finally, the fourth wave has developed self-assembling nanoentities by chemical means.
The present invention represents a fifth generation of self-organizing collectives of intelligent nanorobotics. Self-organizing processes are possible at the nano- and micron-level because of the convergence of nanoelectronics developments and nanomechatronics developments.
While the first four generations of nanotechnology have been developed by theoretical scientists and inventors, the fifth generation of nanotechnology has been largely open until now. The present invention fills the gaps in the literature and in the prior art involving nanorobotics.
Early twentieth century theoretical physicists discovered that the simplest atoms were measurable at the nanometer scale of one billionth of a meter. In 1959, in his lecture “Race to the Bottom,” the physicist Richard Feynman proposed a new science and technology to manipulate molecules at the nanoscale. In the 1970s Drexler's pioneering research into nanotechnology molecular-scale machinery provides a foundation for current research. In 1979, researchers at IBM developed scanning tunneling microscopy (STM) with which they manipulated atoms to spell the letters IBM. Also in the 1970s Ratner and his team at Northwestern developed the first nano-scale transistor-like device for nanoelectronics, which was developed into nanotransistors by researchers at the University of California at Berkeley in 1997. Researchers at Rice, Yale and Penn State were able to connect blocks of nanodevices and nanowires, while researchers at Hewlett Packard and UCLA were able to develop a computer memory system based on nano-assembly. Additionally, government researchers at NASA, NIST, DARPA and Naval Research have ongoing nanotechnology development projects, though these are mainly focused on nanoelectronics challenges. Finally, researchers at MIT, Cal Tech, USC, SUNY, Cornell, Maryland, Illinois and other universities in the U.S. have been joined by overseas researchers in developing novel nanotechnologies in order to meet Feynman's challenge.
Nanotech start-up ventures have sprung up to develop nanoscale crystals, to use as biological labels, for use in tagging proteins and nucleic acids (Quantum Dot) and to develop micro-scale arms and grippers by using MEMS to assemble manufacturing devices (Zyvex). Additionally, Nanosys, Nanometrics, Ultatech, Molecular Electronics, Applied Nanotech and Nanorex are ventures that have emerged to develop products in the nanotechnology market space. Until now, however, most of these businesses have focused son inorganic nanomaterials. Though a new generation of materials science has been aided by these earlier generations of nanotechnologies, the real breakthrough lies in identifying methods of developing intelligent systems at the nano-scale.
The two main models for building nanotechnology applications are the ground up method of building entities, on the one hand, and the bottom down method of shrinking photolithography techniques to the nanoscale. Both models present challenges for scientists.
In the case of the bottom up models, several specialized tools have been required. These include (a) atomic force microscopy (AFM), which uses electronics to measure the force exerted on a probe tip as it moves along a surface, (b) scanning tunneling microscopy (STM), which measures electrical current flowing between a scanning tip and a surface, (c) magnetic force microscopy (MFM), which uses a magnetic tip that scans a surface and (d) nanoscale synthesis (NSL), which constructs nanospheres.
In the case of the top down models, several methods and techniques have been developed, including (a) x-ray lithography, (b) ion beam lithography, (c) dip pen nanolithography (DPN), in which a “reservoir of ‘ink’ (atoms/molecules) is stored on top of the scanning probe tip, which is manipulated across the surface, leaving lines and patterns behind” (Ratner, 2003) and (d) micro-imprint lithography (MIL), which emulates a rubber stamp. Lithography techniques generally require the creation of a mask of a main model, which is then reproduced onto a substrate much like a semiconductor is manufactured. It is primarily through lithographic techniques that mass quantities of nanoentities can be created efficiently and cost-effectively.
The main patents obtained in the U.S. in the field of nanotechnology have focused on nanomaterials, MEMS, micro-pumps, micro-sensors, micro-voltaics, lithography, genetic microarray analysis and nano-drug delivery. Examples of these include a meso-microelectromechanical system package (U.S. Pat. No. 6,859,119), micro-opto-electro-mechanical systems (MOEMS) (U.S. Pat. No. 6,580,858), ion beam lithography system (U.S. Pat. No. 6,924,493), carbon nanotube sensors (U.S. Pat. No. 7,013,708) and microfabricated elastomeric valve and pump systems (U.S. Pat. No. 6,899,137 and U.S. Pat. No. 6,929,030). Finally, patents for a drug targeting system (U.S. Pat. No. 7,025,991) and for a design of artificial genes for use as controls in gene expression analytical system (U.S. Pat. No. 6,943,242), used for a DNA microarray, are applied to biotechnology. For the most part, these patents represent third and fourth generation nanotechnologies.
A new generation of nanotechnologies presents procedures for objects to interact with their environment and solve critical problems on the nano- and micron-scale. This generation of technology involves social intelligence and self-organization capabilities.
Biological analogies help to explain the performance of intelligent or self-organizing nanoentities. In the macro-scale environment, the behaviors of insects provides an important model for understanding how to develop models that emulate social intelligence in which chemical markers (pheromones) are used by individual entities to communicate a social goal. On the micro-scale, microbes and pathogens interoperate with the animal's immune system, in which battles either won or lost determine survival of the host. Other intracellular models show how proteins interact in order to perform a host of functions. At the level of DNA, RNA transcription processes are highly organized methods for developing cellular reproduction. These micromachinery processes and functions occur at the nanoscale and provide useful analogies for nanotechnologies.
In order to draw on these biological system analogies, complexity theory has been developed in recent years. Researchers associated with the Sante Fe Institute have developed a range of theoretical models to merge complexity theory and biologically-inspired processes, including genetic algorithms and collective behavior of economic agents.
Such a new nanotechnology requires distributed computation and communication techniques. It is, moreover, necessary for such a technology to adapt to feedback from its environment. The present invention presents a system in which these operations occur and specifies a range of important applications for electronics, medicine and numerous other areas. The main challenges to this advanced nanotechnology system lie in the discovery of solutions to the problems of limited information, computation, memory, communication, mobility and power.
Challenges
The development of a fifth generation of nanotechnologies faces several challenges. First, the manufacturing of nanoparts is difficult. Second, the assembly of nanoparts into functional devices is a major challenge. Third, the control and management of nanosystems is complex. Since physical properties operate differently at the nano-scale than at the macro-scale, we need to design systems that accommodate these unique physical forces.
The problems to identify include how to:                Build nanorobots        Connect nanodevices        Develop a nanorobotic power source        Develop nanorobotic computation        Develop specific nanorobotic functionality        Develop nanorobotic communication system(s)        Develop multi-functional nanorobotics        Activate nanorobotic functionality        Develop nanorobotic computer programming        Develop an external tracking procedure for a nanorobot        Develop an external activation of a nanorobot        Develop a hybrid control system for nanorobots        Use AI for nanorobots        Obtain environmental inputs via sensors        